Chad Sanderson is passionate about data quality, and fixing the muddy relationship between data producers and consumers. He is a former Head of Data at Convoy, a LinkedIn writer, and a published author. He lives in Seattle, Washington, and is the Chief Operator of the Data Quality Camp. Without data quality, your data initiatives will fail. Despite that, data teams still struggle to gain buy-in on quality initiatives from executive teams. Here's why: 1.

Since leaving university, I have always been involved with data, learning so much during my time as an automation engineer and big data engineer working for an automotive tier 1 manufacturing company and as a data architect for an IT consultancy in the SAP and BI domain. And today, I count myself very fortunate to have a job at Kensu that I am truly passionate about. As a Technical Solution Architect, I get to help organizations with data health and data engineering problems on a daily basis!

A lot has been written about data observability by authors, analysts, and vendors over the past few years as it is becoming an increasingly important component of organizations' data architectures. This blog will examine why organizations need data observability and how they should approach the buying experience/cycle.

Recently I read a very informative article by Stephen Catanzano in Tech Target (Avoid data sprawl with a single source of truth). To be honest, this is an age-old challenge, and it's getting worse. IDC states that by 2025 the global datasphere will grow to 175 Zeta bytes and that 90% of the data in the world is a replica. Why does this matter? As Stephen points out in his article, a single source of truth is a fundamental concept in data management.

Apache Spark has become one of the most popular open-source data processing platforms in the enterprise ecosystem, especially thanks to its ability to handle both batch and real-time data processing on large amounts of data.

We often find it hard to remember the world we left behind, but cast your mind back, say, 20 years, and we lived in a very different world. Personal Computers and the internet were on the rise, and businesses were all becoming connected. This provided companies with immense opportunities in terms of collaboration and digital adoption, and on the flip side, it eased the distribution of computer viruses. Today we barely even think about our antivirus software and policies.

As we move into 2023, I am very excited to see all of the predictions for data and analytics and what they mean to Kensu. I looked at different publications and spoke with various industry experts and analysts to see if there were any conclusions we could draw.

As organizations look to scale up and improve the business value of their growing data volumes, certain data trends have garnered the attention of data and business professionals alike. With this growth promising to continue in the upcoming year, data leaders are looking to implement tools to enrich their organization’s data like never before. Here are seven trends you can watch for in the new year.